School Climate Research: Italian Adaptation and Validation of a Multidimensional School Climate Questionnaire
Bibliographic record
Abstract
In this article, we present a multidimensional school climate questionnaire, based on an adaptation and validation of the Socio-Educational Environment Questionnaire, which is an instrument developed in Canada, assessing several dimensions of school climate. In particular, the aim of this research was to create a Multidimensional School Climate Questionnaire, which is adding to the original measure by testing a second-order factor model. We conducted two studies with different samples of middle school students (aged from 10 to 16 years) from Northern Italy (Study 1: 575 students and Study 2: 1070 students), and collected data on the psychometric features of the instrument, its reliability and validity. In particular, in Study 1, we carried out the adaptation process and an exploratory factor analysis. In Study 2, we conducted first- and second-order confirmatory factor analysis and tested the associations with school engagement and burnout scales. Overall, our results supported the stability of the adaptation and offered further insights into the original instrument. Assessment implications are discussed.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".